Data and technology are the two most important elements of businesses across different industries in this tech-driven world. Hence, Data Analysts have been rated as one of the most in-demand professionals in every industry today. As per the US Bureau of Labour Statistics, the demand for data analysts is expected to grow by 25% from 2020 to 2030.
Data Analysts are the experts who collect and analyse a large volume of unstructured data and capture valuable insights for making profitable business decisions. Companies look for specialised skill sets when hiring Data Analysts for different job positions. So, let’s take a look at the top skills that a Data Analyst professional must possess to achieve professional success.
Key Highlights
- Technical skills required for Data Analyst fresher
- Structured Query Language
- Statistical programming language
- Statistics and Mathematics knowledge
- Machine learning
- Data visualisation
- Data management
- Econometrics
- Soft skills for a Data Analyst
- Popular Data Analytics courses
Technical skills required for Data Analyst fresher
Structured Query Language or SQL: SQL is the standard database language that helps extract, organise, and manage large datasets. SQL coding language involves adding, updating, deleting, or extracting information from a database to draw meaningful business analyses. Thus, matchless knowledge in SQL is a prerequisite skill for different kinds of Data Analyst job roles.
Statistical programming language: R and Python are statistical programming languages that come in handy to perform advanced analysis on big data sets efficiently. An ability to write codes in these languages enables cleaning, analysing as well as visualising large data sets quickly and effectively. Therefore, companies prefer Data Analysts with mastery over one of these open-source languages.
Statistics and Mathematics knowledge: Processing loads of data is a day-to-day task of Data Analysts. With a strong knowledge of mathematics, they can easily understand numbers and combine the data effectively. Similarly, expertise in statistics and probability can be utilised to identify patterns and trends in data and produce accurate results by avoiding logical errors.
Machine Learning (ML) and Artificial Intelligence (AI): AI and ML are critical in Data Science. They focus on building algorithms that are specifically designed to identify patterns and trends in big data sets. Though not every Analyst can work flawlessly with these technological advancements, a Data Analyst proficient in AI and ML gets a competitive advantage during the hiring process for various positions.
Data visualisation: Data visualisation is the ability to present findings interestingly and concisely via charts, maps and graphs. The data visualisation skill helps organisational leaders (with or without having training in Data Analysis) to understand complex business problems and make better decisions. Thus, an ability to present the data in a manner that answers common data-related organisational problems can make you a highly desirable candidate for a Data Analyst role.
Data management: Data management is a step-by-step process of collecting, organising and storing data securely and efficiently to infer growth-oriented business decisions. According to recent research, 80% of the job responsibilities of most data professionals include cleaning and preparing data. Hence, companies expect that even an inexperienced Data Analyst must possess a comprehensive understanding of managing the data.
Econometrics: The branch of economics applies mathematical and statistical data models for understanding historical data and forecasting future trends. Data Analysts looking for jobs in the financial sector must possess an adept understanding of econometrics to build a successful career.
Soft skills for a Data Analyst
Data Analysts require more than technical skills to increase their employability potential and excel in a workplace. Soft skills complement the hard (technical) skills of candidates. Some of the soft skills that employers highly value are as follows:
- Analytical thinking
- Writing and communication skills
- Problem-solving skills
- Attention to detail
- Team player
Popular Data Analytics courses
The demand for Data Analysts in sectors like healthcare, e-commerce, and banking, to name a few, has increased. Here are some popular courses in Data Analytics.
- Probability and Statistical course, University of London
- Master of Statistics, Stanford University
- MSc in Data Analytics, Oxford Brookes University
- MBA in Data Science and Data Analytics, Symbiosis Pune
- Advanced Data Analytics for Managers, IIM Kozhikode
To bridge the skill gap and meet the ever-growing demand for professionals, many reputed educational institutes are offering skilling, upskilling and reskilling courses in addition to mainstream courses in Data Analytics.
So, if you are planning to pursue a Data Analytics course from India, you can opt for an education loan. At Avanse Financial Services, we offer student loans with benefits like 100% finance, quick sanctions, and flexible repayment options. Contact us today to know more about an education loan for study abroad programs.
